Econometric Analysis of Production Networks with Dominant Units

This paper builds on the work of Acemoglu et al. (2012) and considers a production network with unobserved common technological factor and establishes general conditions under which the network structure contributes to aggregate fluctuations. It introduces the notions of strongly and weakly dominant units, and shows that at most a finite number of units in the network can be strongly dominant, while the number of weakly dominant units can rise with N (the cross section dimension). This paper further establishes the equivalence between the highest degree of dominance in a network and the inverse of the shape parameter of the power law. A new extremum estimator for the degree of pervasiveness of individual units in the network is proposed, and is shown to be robust to the choice of the underlying distribution. Using Monte Carlo techniques, the proposed estimator is shown to have satisfactory small sample properties. Empirical applications to US input-output tables suggest the presence of production sectors with a high degree of pervasiveness, but their effects are not sufficiently pervasive to be considered as strongly dominant

Common Factors and Spatial Dependence: An Application to US House Prices

This paper considers panel data models with cross-sectional dependence arising from both spatial autocorrelation and unobserved common factors. It derives conditions for model identification and proposes estimation methods that employ cross-sectional averages as factor proxies, including the 2SLS, Best 2SLS, and GMM estimations. The proposed estimators are robust to unknown heteroskedasticity and serial correlation in the disturbances, unrequired to estimate the number of unknown factors, and computationally tractable. The paper establishes the asymptotic distributions of these estimators and compares their consistency and efficiency properties. Extensive Monte Carlo experiments lend support to the theoretical findings and demonstrate the satisfactory finite sample performance of the proposed estimators. The empirical section of the paper finds strong evidence of spatial dependence of real house price changes across 377 Metropolitan Statistical Areas in the US from 1975Q1 to 2014Q4. The results also reveal that population and income growth have significantly positive direct and spillover effects on house price changes. These findings are robust to different specifications of the spatial weights matrix constructed based on distance, migration flows, and pairwise correlations

Common Factors and Spatial Dependence: An Application to US House Prices

This paper considers panel data models with cross-sectional dependence arising from both spatial autocorrelation and unobserved common factors. It derives conditions for model identification and proposes estimation methods that employ cross-sectional averages as factor proxies, including the 2SLS, Best 2SLS, and GMM estimations. The proposed estimators are robust to unknown heteroskedasticity and serial correlation in the disturbances, unrequired to estimate the number of unknown factors, and computationally tractable. The paper establishes the asymptotic distributions of these estimators and compares their consistency and efficiency properties. Extensive Monte Carlo experiments lend support to the theoretical findings and demonstrate the satisfactory finite sample performance of the proposed estimators. The empirical section of the paper finds strong evidence of spatial dependence of real house price changes across 377 Metropolitan Statistical Areas in the US from 1975Q1 to 2014Q4. The results also reveal that population and income growth have significantly positive direct and spillover effects on house price changes. These findings are robust to different specifications of the spatial weights matrix constructed based on distance, migration flows, and pairwise correlations

Structural Econometric Estimation of the Basic Reproduction Number for Covid-19 Across U.S. States and Selected Countries

This paper proposes a structural econometric approach to estimating the basic reproduction number ($\mathcal{R}_{0}$) of Covid-19. This approach identifies $\mathcal{R}_{0}$ in a panel regression model by filtering out the effects of mitigating factors on disease diffusion and is easy to implement. We apply the method to data from 48 contiguous U.S. states and a diverse set of countries. Our results reveal a notable concentration of $\mathcal{R}_{0}$ estimates with an average value of 4.5. Through a counterfactual analysis, we highlight a significant underestimation of the $\mathcal{R}_{0}$ when mitigating factors are not appropriately accounted for

The Impact of Rental Housing on Neighborhood Racial and Social Integration

Neighborhood racial and class segregation continue to be major social problems within America’s metropolitan areas. Segregation has been linked to a whole host of racial and class inequalities, including access to jobs, schooling and single parenthood, and future earnings. One factor accounting for segregation is the inability of black and lower income households to afford housing in white neighborhoods, where housing units historically have been largely owner-occupied single-family homes. In recent years there has been a shift in the housing makeup of many of these neighborhoods, with rentals and foreclosures increasing in share. This has made housing more affordable in these neighborhoods. In this paper we investigate the impact that foreclosures and three types of rentals (single-family, condominium, and apartments) have on neighborhood racial and income integration using data from Miami-Dade County, Florida. We find that neighborhoods have become more racially and socially integrated as rentals have increased as a share of the housing stock

The Impact of Rental Housing on Neighborhood Racial and Social Integration

Neighborhood racial and class segregation continue to be major social problems within America’s metropolitan areas. Segregation has been linked to a whole host of racial and class inequalities, including access to jobs, schooling and single parenthood, and future earnings. One factor accounting for segregation is the inability of black and lower income households to afford housing in white neighborhoods, where housing units historically have been largely owner-occupied single-family homes. In recent years there has been a shift in the housing makeup of many of these neighborhoods, with rentals and foreclosures increasing in share. This has made housing more affordable in these neighborhoods. In this paper we investigate the impact that foreclosures and three types of rentals (single-family, condominium, and apartments) have on neighborhood racial and income integration using data from Miami-Dade County, Florida. We find that neighborhoods have become more racially and socially integrated as rentals have increased as a share of the housing stock

Cortical brain abnormalities in 4474 individuals with schizophrenia and 5098 control subjects via the enhancing neuro Imaging genetics through meta analysis (ENIGMA) Consortium

BACKGROUND: The profile of cortical neuroanatomical abnormalities in schizophrenia is not fully understood, despite hundreds of published structural brain imaging studies. This study presents the first meta-analysis of cortical thickness and surface area abnormalities in schizophrenia conducted by the ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) Schizophrenia Working Group. METHODS: The study included data from 4474 individuals with schizophrenia (mean age, 32.3 years; range, 11-78 years; 66% male) and 5098 healthy volunteers (mean age, 32.8 years; range, 10-87 years; 53% male) assessed with standardized methods at 39 centers worldwide. RESULTS: Compared with healthy volunteers, individuals with schizophrenia have widespread thinner cortex (left/right hemisphere: Cohen's d = -0.530/-0.516) and smaller surface area (left/right hemisphere: Cohen's d = -0.251/-0.254), with the largest effect sizes for both in frontal and temporal lobe regions. Regional group differences in cortical thickness remained significant when statistically controlling for global cortical thickness, suggesting regional specificity. In contrast, effects for cortical surface area appear global. Case-control, negative, cortical thickness effect sizes were two to three times larger in individuals receiving antipsychotic medication relative to unmedicated individuals. Negative correlations between age and bilateral temporal pole thickness were stronger in individuals with schizophrenia than in healthy volunteers. Regional cortical thickness showed significant negative correlations with normalized medication dose, symptom severity, and duration of illness and positive correlations with age at onset. CONCLUSIONS: The findings indicate that the ENIGMA meta-analysis approach can achieve robust findings in clinical neuroscience studies; also, medication effects should be taken into account in future genetic association studies of cortical thickness in schizophrenia

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Nanoarchitectured Array Electrodes for Rechargeable Lithium- and Sodium-Ion Batteries

Rechargeable ion batteries have contributed immensely to shaping the modern world and been seriously considered for the efficient storage and utilization of intermittent renewable energies. To fulfill their potential in the future market, superior battery performance of high capacity, great rate capability, and long lifespan is undoubtedly required. In the past decade, along with discovering new electrode materials, the focus has been shifting more and more toward rational electrode designs because the performance is intimately connected to the electrode architectures, particularly their designs at the nanoscale that can alleviate the reliance on the materials' intrinsic nature. The utilization of nanoarchitectured arrays in the design of electrodes has been proven to significantly improve the battery performance. A comprehensive summary of the structural features and fabrications of the nanoarchitectured array electrodes is provided, and some of the latest achievements in the area of both lithium‐ and sodium‐ion batteries are highlighted. Finally, future challenges and opportunities that would allow further development of such advanced electrode configuration are discussed

Cardiovascular disease, chronic kidney disease, and diabetes mortality burden of cardiometabolic risk factors from 1980 to 2010: A comparative risk assessment

Background: High blood pressure, blood glucose, serum cholesterol, and BMI are risk factors for cardiovascular diseases and some of these factors also increase the risk of chronic kidney disease and diabetes. We estimated mortality from cardiovascular diseases, chronic kidney disease, and diabetes that was attributable to these four cardiometabolic risk factors for all countries and regions from 1980 to 2010. Methods: We used data for exposure to risk factors by country, age group, and sex from pooled analyses of population-based health surveys. We obtained relative risks for the effects of risk factors on cause-specific mortality from meta-analyses of large prospective studies. We calculated the population attributable fractions for each risk factor alone, and for the combination of all risk factors, accounting for multicausality and for mediation of the effects of BMI by the other three risks. We calculated attributable deaths by multiplying the cause-specific population attributable fractions by the number of disease-specific deaths. We obtained cause-specific mortality from the Global Burden of Diseases, Injuries, and Risk Factors 2010 Study. We propagated the uncertainties of all the inputs to the final estimates. Findings: In 2010, high blood pressure was the leading risk factor for deaths due to cardiovascular diseases, chronic kidney disease, and diabetes in every region, causing more than 40% of worldwide deaths from these diseases; high BMI and glucose were each responsible for about 15% of deaths, and high cholesterol for more than 10%. After accounting for multicausality, 63% (10·8 million deaths, 95% CI 10·1-11·5) of deaths from these diseases in 2010 were attributable to the combined effect of these four metabolic risk factors, compared with 67% (7·1 million deaths, 6·6-7·6) in 1980. The mortality burden of high BMI and glucose nearly doubled from 1980 to 2010. At the country level, age-standardised death rates from these diseases attributable to the combined effects of these four risk factors surpassed 925 deaths per 100 000 for men in Belarus, Kazakhstan, and Mongolia, but were less than 130 deaths per 100 000 for women and less than 200 for men in some high-income countries including Australia, Canada, France, Japan, the Netherlands, Singapore, South Korea, and Spain. Interpretation: The salient features of the cardiometabolic disease and risk factor epidemic at the beginning of the 21st century are high blood pressure and an increasing effect of obesity and diabetes. The mortality burden of cardiometabolic risk factors has shifted from high-income to low-income and middle-income countries. Lowering cardiometabolic risks through dietary, behavioural, and pharmacological interventions should be a part of the global response to non-communicable diseases. Funding: UK Medical Research Council, US National Institutes of Health. © 2014 Elsevier Ltd